The BIOM format is designed for general use in broad areas of comparative -omics. For example, in marker-gene surveys, the primary use of this format is to represent OTU tables: the observations in this case are OTUs and the matrix contains counts corresponding to the number of times each OTU is observed in each sample. With respect to metagenome data, this format would be used to represent metagenome tables: the observations in this case might correspond to SEED subsystems, and the matrix would contain counts corresponding to the number of times each subsystem is observed in each metagenome. Similarly, with respect to genome data, this format may be used to represent a set of genomes: the observations in this case again might correspond to SEED subsystems, and the counts would correspond to the number of times each subsystem is observed in each genome.

There are two components to the BIOM project: first is the definition of the BIOM format, and second is development of support objects in multiple programming languages to support the use of BIOM in diverse bioinformatics applications. The version of the BIOM file format is independent of the version of the biom-format software.

There are official implementations of BIOM format support objects (APIs) in the Python and R programming languages. The rest of this site contains details about the BIOM file format (which is independent of the API) and the Python biom-format API. For more details about the R API, please see the CRAN biom package.

To install the biom-format project, you can download the latest version here, or work with the development version. Generally we recommend working with the release version as it will be more stable, but if you want access to the latest features (and can tolerate some instability) you should work with the development version.

The easiest way to install the latest version of the biom-format project and its required dependencies is via pip:

pip install numpy
pip install biom-format

That’s it!

If you decided not to install biom-format using pip, it is also possible to manually install the latest release. We’ll illustrate the install process in the $HOME/code directory. You can either work in this directory on your system (creating it, if necessary, by running mkdir$HOME/code) or replace all occurrences of $HOME/code in the following instructions with your working directory. Please note that numpy must be in your installed prior to installing biom-format. Change to this directory to start the install process:

To install (either the development or release version), follow these steps:

sudo python setup.py install

If you do not have sudo access on your system (or don’t want to install the biom-format project in the default location) you’ll need to install the library code and scripts in specified directories, and then tell your system where to look for those files. You can do this as follows:

The biom command referenced in the previous section is a driver for commands in biom-format, powered by the pyqi project. You can enable tab completion of biom command names and command options (meaning that when you begin typing the name of a command or option you can auto-complete it by hitting the tab key) by following a few simple steps from the pyqi documentation. While this step is optional, tab completion is very convenient so it’s worth enabling.

To enable tab completion, follow the steps outlined under Configuring bash completion in the pyqi install documentation, substituting biom for my-project and my_project in all commands. After completing those steps and closing and re-opening your terminal, auto-completion should be enabled.

There is also a BIOM format package for R, called biom. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object, as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the python API and other tools included with the biom-format project, but with a decidedly “R flavor” that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.

To install the latest stable release of the biom package enter the following command from within an R session:

install.packages("biom")

To install the latest development version of the biom package, enter the following lines in an R session:

install.packages("devtools")# if not already installedlibrary("devtools")install_github("biom","joey711")

The biom-format project was conceived of and developed by the QIIME, MG-RAST, and VAMPS development groups to support interoperability of our software packages. If you have questions about the biom-format project you can contact gregcaporaso@gmail.com.